%0 Journal Article
%T GrassmannOptim: An R Package for Grassmann Manifold Optimization
%A Ko Placid Adragni
%A R. Dennis Cook
%A Seongho Wu
%J Journal of Statistical Software
%D 2012
%I University of California, Los Angeles
%X The optimization of a real-valued objective function f(U), where U is a p X d,p > d, semi-orthogonal matrix such that UTU=Id, and f is invariant under right orthogonal transformation of U, is often referred to as a Grassmann manifold optimization. Manifold optimization appears in a wide variety of computational problems in the applied sciences. In this article, we present GrassmannOptim, an R package for Grassmann manifold optimization. The implementation uses gradient-based algorithms and embeds a stochastic gradient method for global search. We describe the algorithms, provide some illustrative examples on the relevance of manifold optimization and finally, show some practical usages of the package.
%K Grassmann manifold
%K constrained optimization
%K simulated annealing
%U http://www.jstatsoft.org/v50/i05/paper